library(ggmap)

qmap("Mannheim")

MA_map <- qmap("Mannheim",zoom=14)

qmap(location = 'Mannheim', zoom = 12)

qmap(location = 'Mannheim', zoom = 13)

qmap(location = 'Mannheim', zoom = 20)

qmap(location = 'Mannheim', zoom = 14, source="osm")

qmap(location = 'Mannheim', zoom = 14, maptype="satellite")

qmap(location = 'Mannheim', zoom = 14, maptype="hybrid")

qmap(location = 'Mannheim', zoom = 14,
 maptype="toner",source="stamen")

• qmap is a wrapper for ggmap and get_map
• with get_googlemap you get similar results

MAmap <- get_googlemap("Mannheim")
ggmap(MAmap)

Geocoding (…) uses a description of a location, most typically a postal address or place name, to find geographic coordinates from spatial reference data …

Wikipedia - Geocoding

geocode("Mannheim University")

POI1 <- geocode("B2, 1 Mannheim")
POI2 <- geocode("Hbf Mannheim")
POI3 <- geocode("Wasserturm Mannheim")

POI <- c("B2, 1 Mannheim","Hbf Mannheim",
         "Wasserturm Mannheim")

ListPOI <- data.frame(lat=NA,lon=NA)

for ( i in 1:length(POI)){
  geoPOI <- geocode(POI[i])
  ListPOI[i,"lat"] <-  geoPOI$lat 
  ListPOI[i,"lon"] <-  geoPOI$lon 
}

Article by David Kahle and Hadley Wickham on the usage of ggmap.

MA_map +
geom_point(aes(x = lon, y = lat),
data = ListPOI)

• Usage of geom_point
• Question on stackoverflow

ListPOI$color <- c("A","B","C")
MA_map +
geom_point(aes(x = lon, y = lat,col=color),
data = ListPOI)

ListPOI$size <- c(10,20,30)
MA_map +
geom_point(aes(x = lon, y = lat,col=color,size=size),
data = ListPOI)

• Cheatsheet on data visualisation

mapdist("Q1, 4 Mannheim","B2, 1 Mannheim")

##             from             to   m    km     miles seconds  minutes
## 1 Q1, 4 Mannheim B2, 1 Mannheim 746 0.746 0.4635644     200 3.333333
##        hours
## 1 0.05555556

mapdist("Q1, 4 Mannheim","B2, 1 Mannheim",mode="walking")

##             from             to   m    km     miles seconds  minutes
## 1 Q1, 4 Mannheim B2, 1 Mannheim 546 0.546 0.3392844     421 7.016667
##       hours
## 1 0.1169444

mapdist("Q1, 4 Mannheim","B2, 1 Mannheim",mode="bicycling")

##             from             to   m    km    miles seconds  minutes
## 1 Q1, 4 Mannheim B2, 1 Mannheim 555 0.555 0.344877     215 3.583333
##        hours
## 1 0.05972222

library(geosmdata2)
xml_obj <- get_osm_nodes("bakery","Berlin")
info <- extract_info_op(xml_obj,"bakery")

library(ggmap)
Imap <- qmap(location = "Berlin", zoom = 10, maptype="toner",source="stamen")
Imap

The example is taken from here

Imap + geom_density2d(data = info, aes(x = lon, y = lat),lwd=1.5)